What is Data Classification? Here’s What You Need to Know
We’ll be looking at the different types of data classification and how to effectively classify your data.
A Definition of Data Classification
Data classification is the way that data is organized and used in a business. It helps to make it easier for people to find what they need when they need it.
Data classification is a way to organize data so that it can be found and tracked more easily. It also saves money because you don’t have as much duplicated data, which speeds up the search process.
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Reasons for Data Classification
When data is classified, it can be more easily protected or accessed. It also helps to meet certain regulatory requirements.
Types of Data Classification
The data classification process often involves a variety of tags and labels that define the type of data, its confidentiality level, and integrity. Availability may also be considered in the data classification processes.
There are three types of data classification that people use in the industry: public, private and confidential.
- Content-based classification is an examination of files with the goal to find sensitive information.
- Context-based classification looks at indirect indicators of sensitive information to determine if an email or document should be classified as secret, confidential, etc.
- User-based classification is based on a person’s discretion and knowledge. They have to know what the document contains, which can be difficult because they may not know or understand it.
There are many different approaches to content, context, and user-based data. It depends on the company’s needs or what type of data they’re working with.
Determining Data Risk
It’s important to determine the relative risk associated with data types, how they are handled and where they are stored. Data can be classified into three levels of risk.
- Data that is public and easy to recover are likely less risky than data collection methods with higher risks.
- This is data that’s not public or used internally (by your organization andor partners). However, it’s also not too sensitive to be “high risk.” Proprietary operating procedures, cost of goods and some company documentation may fall into this category.Article: When I first began hiring salespeople, I just assumed pay along with commissions and bonuses would be enough sales motivation.
- Anything that’s sensitive or crucial to the security of your company falls into this category. Also, any data that is extremely difficult to recover if lost would fall under high risk.
It’s also important to note that some companies use a more granular scale, adding “severe risk” or other categories.
Using a Data Classification Matrix
Creating and labeling data may be easy for some organizations. If there are a small number of different types, or your company has fewer transactions, determining the risk is likely less difficult. That said, many companies with high volume or multiple types need to use a comprehensive way of assessing their risks.
By creating a matrix of data andor systems, you can quickly determine how to better classify and protect sensitive information.
An Example of Data Classification
There are three types of classification, public data being the least sensitivesecure. Restricted is more secure and private being most.
The Data Classification Process
Data classification can be difficult and tedious. Automated systems to help streamline the process exist, but an enterprise must determine what categories and criteria will be used for data classification, understand their objectives when classifying data (what they need it for), outline who is responsible in maintaining proper practices with this process, implement security standards that correspond to these categories of classified data.
Policies and procedures should be well-defined, including the security of confidential data. Employees promoting compliance to policies need straightforward instructions that can easily be interpreted.
GDPR Data Classification
With the General Data Protection Regulation (GDPR) in effect, companies need to classify their data so that it’s easy for them to know what information is covered by GDPR. They have to do this before they start storing or transferring any of the classified data.
GDPR also makes it illegal to process personal data related to race, ethnicity or political opinion. This can help reduce the risk of compliance issues.
Steps for Effective Data Classification
- Classifying data properly starts with a careful examination of the current setup, including where your data is and what regulations apply to it. You need to know all about the information you have before classifying it.
- Creating a data classification policy is the first step in staying compliant with principles for protecting your organization’s sensitive information.
- Now that you have a policy and an idea of what data is out there, it’s time to classify the data. Decide on how sensitive or private each piece of information will be.
Data classification is important for making sense of the vast amount of data available.
Data classification provides a clear picture of all data within an organization’s control and where it is stored. This helps employees find the information they need to do their jobs, as well as keep track on how to protect that data from potential security risks.
Protect Your Organization from Cybersecurity Threats
SecurityStudio help information security leaders at organizations ensure they’re protected against cybersecurity threats, stay insurable, and legally defensible with our risk assessment and risk management software. Schedule a demo to learn how we can help.
We’ll be looking at the different types of data classification and how to effectively classify your data.
